Breath Ammonia Is a Useful Biomarker Predicting Kidney Function in Chronic Kidney Disease Patients

Noninvasive Diagnosis of Early-Stage Chronic Kidney Disease and Monitoring of the Hemodialysis Process in Clinical Practice via Exhaled Breath Analysis Using an Ultrasensitive Flexible NH3 Sensor Assisted by Pattern Recognition

To achieve the early diagnosis of chronic kidney disease (CKD), noninvasive hemodialysis monitoring, and accurate determination of dialysis duration and adequacy, a noninvasive, point-of-care, user-friendly device should be developed. Here, a flexible, room temperature NH3 gas sensor sensitive to the key breath biomarkers of CKD─NH3 and creatinine─was fabricated. The sensor had detection limits of 100 ppb for NH3 and 1 ppm for creatinine. Clinically, a total of 96 exhaled breath samples, half from 39 CKD patients and the other half from 48 healthy controls were collected and analyzed. With the assistance of a pattern recognition algorithm , the early diagnosis of CKD was achieved by the sensor, with PCA being used due to sensor's cross-sensitivity to CKD biomarkers. Diagnostic models distinguishing CKD versus non-CKD and early-stage CKD versus advanced-stage CKD were constructed using the SVM algorithm, achieving an overall accuracy of 0.93 and 0.94, with area under the curve (AUC) values of 0.97 and 0.99 for all subjects in receiver operating characteristic (ROC) analysis, respectively. The hemodialysis processes of patients were monitored in real-time, with the sensor response values exhibiting ideal exponential decay over time. The sensor response values showed a strong positive correlation with serum creatinine levels (r = 0.85) and a moderate positive correlation with blood urea nitrogen levels (r = 0.62), both of which are key clinical diagnostic indicators for CKD. These are good results, as 54% of CKD samples are from early-stage CKD patients. These results suggest that the sensor could serve as a noninvasive alternative to traditional blood tests for renal function evaluation and CKD diagnosis. Overall, this sensor demonstrates great potential in clinical practice for early diagnosis of CKD, monitoring the daily health status of CKD patients, optimizing the dialysis schedule, and monitoring the dialysis process in real-time.

Advancements in Breathomics: Special Focus on Electrochemical Sensing and AI for Chronic Disease Diagnosis and Monitoring

This Review examines the potential of breathomics in enhancing disease monitoring and diagnostic precision when integrated with artificial intelligence (AI) and electrochemical sensing techniques. It discusses breathomics' potential for early and noninvasive disease diagnosis with a focus on chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), and lung cancer, which have been well studied in the context of VOC association with diseases. The noninvasive nature of exhaled breath analysis can be advantageous compared to traditional diagnostic methods for CKD, which often rely on blood and urine testing. VOC analysis can enhance spirometry and imaging methods used in COPD diagnosis, providing a more comprehensive picture of the disease's progression. Breathomics could also provide a less intrusive and potentially earlier diagnostic approach for lung cancer, which is now dependent on imaging and biopsy. The combination of breathomics, electrochemical sensing, and AI could lead to more personalized and successful treatment plans for chronic illnesses using AI algorithms to decipher complicated VOC patterns. This Review assesses the viability and effectiveness of combining breathomics with electrochemical sensors and artificial intelligence by synthesizing recent research findings and technological developments.

Quartz-Enhanced Photoacoustic Spectroscopy-Based Acetone and Ammonia Measurements from Human Breath Near 8 μm Wavelength Band

Human breath gas analysis is a noninvasive disease diagnostic approach used to identify different pathological conditions in the human body. Monitoring breath acetone (C3H6O) and ammonia (NH3) as biomarkers is vital in diagnosing diabetes mellitus and liver disorders, respectively. In this article, the quartz-enhanced photoacoustic spectroscopy (QEPAS) technique is proposed and demonstrated for measuring C3H6O and NH3 in human exhaled breath samples. We present the QEPAS technique-based approach combined with a broadband tunable quantum cascade laser (QCL) operating from 7.9 to 8.4 μm to target both C3H6O and NH3 at specific absorption wavelengths. The experimental results show that minimum detection limits (MDLs) of 57 and 190 ppb were achieved for C3H6O and NH3, respectively. The proposed technique measured C3H6O and NH3 biomarkers in human breath samples collected from volunteers. The concentration measurements of exhaled breath biomarkers using the QEPAS technique in the 8 μm spectral region agreed with the blood glucose and blood ammonia measurements. The measurement limit and sensitivity met the requirement of the breath gas analysis needed to distinguish the concentrations obtained from a healthy person from those of a person with diabetes and liver disorder conditions.

A Facile Way to Simultaneously Improve Humidity-Immunity and Gas Response in Semiconductor Metal Oxide Sensors

The metal-oxide-based gas sensors show great potential in exhaled breath analysis owing to their simple, fast, and noninvasive characteristics. However, the exhaled breath contains moisture, and the surface-active sites of metal oxides are easily poisoned by water molecules, leading to degradation of the sensor performance, particularly the gas response and selectivity. Therefore, it is essential to develop oxide sensors that can reliably sense target gases over a wide humidity range without sacrificing the gas response. In this study, a facile strategy was proposed to incorporate hydrophobic La into an oxide sensor to simultaneously improve the humidity-stability and sensitivity of NH3 detection for early prediction of kidney failure. WO3 sensors doped with various concentrations of La were successfully synthesized, and their gas-sensing performances under various humid conditions were systematically investigated. Interestingly, a small amount of La doping (1 at. %) effectively prevented water poisoning and improved the gas response simultaneously. This sensor was able to selectively detect NH3 up to 200 ppb with a limit of detection (LOD) of ∼780 ppt over a wide range of humidity. The concurrent enhancement in gas response and humidity-immunity was attributed to the surface hydrophobicity and increased specific surface area caused by the incorporation of La.

Machine Learning Model Discriminate Ischemic Heart Disease Using Breathome Analysis

Background: Ischemic heart disease (IHD) impacts the quality of life and is the most frequently reported cause of morbidity and mortality globally. Aims: To assess the changes in the exhaled volatile organic compounds (VOCs) in patients with vs. without ischemic heart disease (IHD) confirmed by stress computed tomography myocardial perfusion (CTP) imaging. Objectives: IHD early diagnosis and management remain underestimated due to the poor diagnostic and therapeutic strategies including the primary prevention methods. Materials and Methods: A single center observational study included 80 participants. The participants were aged ≥ 40 years and given an informed written consent to participate in the study and publish any associated figures. Both groups, G1 (n = 31) with and G2 (n = 49) without post stress-induced myocardial perfusion defect, passed cardiologist consultation, anthropometric measurements, blood pressure and pulse rate measurements, echocardiography, real time breathing at rest into PTR-TOF-MS-1000, cardio-ankle vascular index, bicycle ergometry, and immediately after performing bicycle ergometry repeating the breathing analysis into the PTR-TOF-MS-1000, and after three minutes from the end of the second breath, repeat the breath into the PTR-TOF-MS-1000, then performing CTP. LASSO regression with nested cross-validation was used to find the association between the exhaled VOCs and existence of myocardial perfusion defect. Statistical processing performed with R programming language v4.2 and Python v.3.10 [^R], STATISTICA program v.12, and IBM SPSS v.28. Results: The VOCs specificity 77.6% [95% confidence interval (CI); 0.666; 0.889], sensitivity 83.9% [95% CI; 0.692; 0.964], and diagnostic accuracy; area under the curve (AUC) 83.8% [95% CI; 0.73655857; 0.91493173]. Whereas the AUC of the bicycle ergometry 50.7% [95% CI; 0.388; 0.625], specificity 53.1% [95% CI; 0.392; 0.673], and sensitivity 48.4% [95% CI; 0.306; 0.657]. Conclusions: The VOCs analysis appear to discriminate individuals with vs. without IHD using machine learning models. Other: The exhaled breath analysis reflects the myocardiocytes metabolomic signature and related intercellular homeostasis changes and regulation perturbances. Exhaled breath analysis poses a promise result to improve the diagnostic accuracy of the physical stress tests using machine learning models.

Recent Progress on Perovskite Materials for VOC Gas Sensing

Volatile organic compound (VOC) gases are highly hazardous to human health, and their presence in the human breath plays an indispensable role for the early diagnosis of various diseases (cancer, renal failure, etc.). In recent times, perovskite materials have shown notable performance in the detection of VOC gases with high accuracy, fast response, recovery time, selectivity, and sensitivity, owing to their unique crystallographic structures and excellent optoelectronic properties. In this Review, we look at recent reports on perovskite-based sensors and their sensing performance toward VOC gases. Here, we focus on the sensing mechanisms of two types of perovskite materials, metal halide and metal oxide perovskites, and explain the differences in their crystal structures. We also discuss the common preparation methods used by researchers for the synthesis of these perovskite materials. Further, we elucidate various important factors influencing the sensing performance of perovskite-based sensors, such as doping, defects, morphology, temperature, humidity, and light. We conclude with the future prospects and challenges related to these perovskite-based sensors toward the detection of VOC gases.

Non-Invasive Diagnostic Approaches for Kidney Disease: The Role of Electronic Nose Systems

Kidney diseases are a group of conditions related to the functioning of kidneys, which are in turn unable to properly filter waste and excessive fluids from the blood, resulting in the presence of dangerous levels of electrolytes, fluids, and waste substances in the human body, possibly leading to significant health effects. At the same time, the toxins amassing in the organism can lead to significant changes in breath composition, resulting in halitosis with peculiar features like the popular ammonia breath. Starting from this evidence, scientists have started to work on systems that can detect the presence of kidney diseases using a minimally invasive approach, minimizing the burden to the individuals, albeit providing clinicians with useful information about the disease's presence or its main related features. The electronic nose (e-nose) is one of such tools, and its applications in this specific domain represent the core of the present review, performed on articles published in the last 20 years on humans to stay updated with the latest technological advancements, and conducted under the PRISMA guidelines. This review focuses not only on the chemical and physical principles of detection of such compounds (mainly ammonia), but also on the most popular data processing approaches adopted by the research community (mainly those relying on Machine Learning), to draw exhaustive conclusions about the state of the art and to figure out possible cues for future developments in the field.

Phase-Engineered MoSe2/CeO2 Composites for Room-Temperature Gas Sensing with a Drastic Discrimination of NH3 and TEA Gases

Detecting and distinguishing between hazardous gases with similar odors by using conventional sensor technology for safeguarding human health and ensuring food safety are significant challenges. Bulky, costly, and power-hungry devices, such as that used for gas chromatography-mass spectrometry (GC-MS), are widely employed for gas sensing. Using a single chemiresistive semiconductor or electric nose (e-nose) gas sensor to achieve this objective is difficult, mainly because of its selectivity issue. Thus, there is a need to develop new materials with tunable and versatile sensing characteristics. Phase engineering of two-dimensional materials to better utilize their physiochemical properties has attracted considerable attention. Here, we show that MoSe2 phase-transition/CeO2 composites can be effectively used to distinguish ammonia (NH3) and triethylamine (TEA) at room temperature. The phase transition of nanocomposite samples from semimetallic (1T) to semiconducting (2H) prepared at different synthesis temperatures is confirmed via X-ray photoelectron spectroscopy (XPS). A composite sensor in which the 2H phase of MoSe2 is predominant lacks discrimination capability and is less responsive to NH3 and TEA. An MoSe2/CeO2 composite sensor with a higher 1T phase content exhibits high selectivity for NH3, whereas one with a higher 2H phase content (2H > 1T) shows more selective behavior toward TEA. For example, for 50% relative humidity, the MoSe2/CeO2 sensor's signal changes from the baseline by 45% and 58% for 1 ppm of NH3 and TEA, respectively, indicating a low limit of detection (LOD) of 70 and 160 ppb, respectively. The composites' superior sensing characteristics are mainly attributed to their large specific surface area, their numerous active sites, presence of defects, and the n-n type heterojunction between MoSe2 and CeO2. The sensing mechanism is elucidated using Raman spectroscopy, XPS, and GC-MS results. Their phase-transition characteristics render MoSe2/CeO2 sensors promising for use in distributed, low-cost, and room-temperature sensor networks, and they offer new opportunities for the development of integrated advanced smart sensing technologies for environmental and healthcare.

Resistive gas sensors for the detection of NH3gas based on 2D WS2, WSe2, MoS2, and MoSe2: a review

Transition metal dichalcogenides (TMDs) with a two-dimensional (2D) structure and semiconducting features are highly favorable for the production of NH3gas sensors. Among the TMD family, WS2, WSe2, MoS2, and MoSe2exhibit high conductivity and a high surface area, along with high availability, reasons for which they are favored in gas-sensing studies. In this review, we have discussed the structure, synthesis, and NH3sensing characteristics of pristine, decorated, doped, and composite-based WS2, WSe2, MoS2, and MoSe2gas sensors. Both experimental and theoretical studies are considered. Furthermore, both room temperature and higher temperature gas sensors are discussed. We also emphasized the gas-sensing mechanism. Thus, this review provides a reference for researchers working in the field of 2D TMD gas sensors.

Ammonia Detection by Electronic Noses for a Safer Work Environment

Providing employees with proper work conditions should be one of the main concerns of any employer. Even so, in many cases, work shifts chronically expose the workers to a wide range of potentially harmful compounds, such as ammonia. Ammonia has been present in the composition of products commonly used in a wide range of industries, namely production in lines, and also laboratories, schools, hospitals, and others. Chronic exposure to ammonia can yield several diseases, such as irritation and pruritus, as well as inflammation of ocular, cutaneous, and respiratory tissues. In more extreme cases, exposure to ammonia is also related to dyspnea, progressive cyanosis, and pulmonary edema. As such, the use of ammonia needs to be properly regulated and monitored to ensure safer work environments. The Occupational Safety and Health Administration and the European Agency for Safety and Health at Work have already commissioned regulations on the acceptable limits of exposure to ammonia. Nevertheless, the monitoring of ammonia gas is still not normalized because appropriate sensors can be difficult to find as commercially available products. To help promote promising methods of developing ammonia sensors, this work will compile and compare the results published so far.

Ammonia detection: A pathway towards potential point-of-care diagnostics

Invasive methods such as blood collection and biopsy are commonly used for testing liver and kidney function, which are painful, time-consuming, require trained personnel, and may not be easily accessible to people for their routine checkup. Early diagnosis of liver and kidney diseases can prevent severe symptoms and ensure better management of these patients. Emerging approaches such as breath and sweat analysis have shown potential as non-invasive methods for disease diagnosis. Among the many markers, ammonia is often used as a biomarker for the monitoring of liver and kidney functions. In this review we provide an insight into the production and expulsion of ammonia gas in the human body, the different diseases that could potentially use ammonia as biomarker and analytical devices such as chemiresistive gas sensors for non-invasive monitoring of this gas. The review also provides an understanding into the different materials, doping agents and substrates used to develop such multifunctional sensors. Finally, the current challenges and the possible future trends have been discussed.

The Challenges and Opportunities for TiO2 Nanostructures in Gas Sensing

Chemiresistive gas sensors based on metal oxides have been widely applied in industrial monitoring, medical diagnosis, environmental pollutant detection, and food safety. To further enhance the gas sensing performance, researchers have worked to modify the structure and function of the material so that it can adapt to different gas types and environmental conditions. Among the numerous gas-sensitive materials, n-type TiO2 semiconductors are a focus of attention for their high stability, excellent biosafety, controllable carrier concentration, and low manufacturing cost. This Perspective first introduces the sensing mechanism of TiO2 nanostructures and composite TiO2-based nanomaterials and then analyzes the relationship between their gas-sensitive properties and their structure and composition, focusing also on technical issues such as doping, heterojunctions, and functional applications. The applications and challenges of TiO2-based nanostructured gas sensors in food safety, medical diagnosis, environmental detection, and other fields are also summarized in detail. Finally, in the context of their practical application challenges, future development technologies and new sensing concepts are explored, providing new ideas and directions for the development of multifunctional intelligent gas sensors in various application fields.

Breath volatile organic compounds for chronic kidney disease progression monitoring

Breath analysis may provide a convenient and non-invasive method for clinical monitoring of chronic kidney disease (CKD) progression. However, few breath volatile organic compounds (VOCs) indicating progression of CKD have been reported. In this study, we used gas chromatography-mass spectrometry (GC-MS) for untargeted detection of breath VOCs in stage 1, 3, and 5 CKD patients. The results showed that, the levels of breath 4-heptanone, n-octane, and n-dodecane gradually increased from CKD stage 1 to stage 5, and their increasing rates from CKD stage 3 to stage 5 were higher than those from CKD stage 1 to stage 3. Gender, smoking habits, age, and body mass index (BMI) had insignificant impact on the levels of the three breath VOCs. The accuracies of the polynomial support vector machine (SVM) and K-nearest neighbour (KNN) models based on 4-heptanone + n-octane + n-dodecane combination in distinguishing CKD stages 1, 3, and 5 were 76.3% and 72.8%, respectively. The combination of 4-heptanone + n-octane + n-dodecane was superior to any single component for monitoring CKD progression. These discoveries have valuable implications for long-term clinical monitoring of CKD and improving our understanding of CKD.

Wireless Detection of Trace Ammonia: A Chronic Kidney Disease Biomarker

Elevated levels of ammonia in breath can be linked to medical complications, such as chronic kidney disease (CKD), that disturb the urea balance in the body. However, early stage CKD is usually asymptomatic, and mass screening is hindered by high instrumentation and operation requirements and accessible and reliable detection methods for CKD biomarkers, such as trace ammonia in breath. Enabling methods would have significance in population screening for early stage CKD patients. We herein report a method to effectively immobilize transition metal selectors in close proximity to a single-walled carbon nanotube (SWCNT) surface using pentiptycene polymers containing metal-chelating backbone structures. The robust and modular nature of the pentiptycene metallopolymer/SWCNT complexes creates a platform that accelerates sensor discovery and optimization. Using these methods, we have identified sensitive, selective, and robust copper-based chemiresistive ammonia sensors that display low parts per billion detection limits. We have added these hybrid materials to the resonant radio frequency circuits of commercial near-field communication (NFC) tags to achieve robust wireless detection of ammonia at physiologically relevant levels. The integrated devices offer a noninvasive and cost-effective approach for early detection and monitoring of CKD.

Non-invasive detection of renal disease biomarkers through breath analysis

Breath biomarkers are substances found in exhaled breath that can be used for non-invasive diagnosis and monitoring of medical conditions, including kidney disease. Detection techniques include mass spectrometry (MS), gas chromatography (GC), and electrochemical sensors. Biosensors, such as GC-MS or electronic nose (e-nose) devices, can be used to detect volatile organic compounds (VOCs) in exhaled breath associated with metabolic changes in the body, including the kidneys. E-nose devices could provide an early indication of potential kidney problems through the detection of VOCs associated with kidney dysfunction. This review discusses the sources of breath biomarkers for monitoring renal disease during dialysis and different biosensor approaches for detecting exhaled breath biomarkers. The future of using various types of biosensor-based real-time breathing diagnosis for renal failure is also discussed.

Breathomics Detect the Cardiovascular Disease: Delusion or Dilution of the Metabolomic Signature

Volatile organic compounds (VOCs) can be subdivided into exogenous and endogenous categories based on their origin. Analyzing the endogenous VOCs can provide insights into maintaining the internal organs' homeostasis. Despite the ongoing development and the current understanding, studies have suggested a link between cardiovascular metabolic alterations in patients with ischemic heart disease and elevated levels of ethane and isoprene detectable through exhaled breath analysis. Conversely, patients with chronic heart failure exhibit elevated acetone and pentane in their exhaled air. These substances originate from disturbances in the heart tissue, including cellular and subcellular modulations. Hypothetically, ethane levels in the exhaled breath analysis can demonstrate the severity of ischemic heart disease and, consequently, the risk of death in the next 10 years due to cardiovascular disease (CVD). Real-time direct mass spectrometry is the preferred method for assessing VOCs in exhaled breath analysis. The accuracy of this analysis depends on several factors, including the selection of the relevant breath fraction, the type of breath collection container (if used), and the pre-concentration technique.

Volatilome is Inflammasome- and Lipidome-dependent in Ischemic Heart Disease

Ischemic heart disease (IHD) is a pathology of global interest because it is widespread and has high morbidity and mortality. IHD pathophysiology involves local and systemic changes, including lipidomic, proteomic, and inflammasome changes in serum plasma. The modulation in these metabolites is viable in the pre-IHD, during the IHD period, and after management of IHD in all forms, including lifestyle changes and pharmacological and surgical interventions. Therefore, these biochemical markers (metabolite changes; lipidome, inflammasome, proteome) can be used for early prevention, treatment strategy, assessment of the patient's response to the treatment, diagnosis, and determination of prognosis. Lipidomic changes are associated with the severity of inflammation and disorder in the lipidome component, and correlation is related to disturbance of inflammasome components. Main inflammasome biomarkers that are associated with coronary artery disease progression include IL-1β, Nucleotide-binding oligomerization domain- like receptor family pyrin domain containing 3 (NLRP3), and caspase-1. Meanwhile, the main lipidome biomarkers related to coronary artery disease development involve plasmalogen lipids, lysophosphatidylethanolamine (LPE), and phosphatidylethanolamine (PE). The hypothesis of this paper is that the changes in the volatile organic compounds associated with inflammasome and lipidome changes in patients with coronary artery disease are various and depend on the severity and risk factor for death from cardiovascular disease in the time span of 10 years. In this paper, we explore the potential origin and pathway in which the lipidome and or inflammasome molecules could be excreted in the exhaled air in the form of volatile organic compounds (VOCs).

An Investigation on the Acetone and Ethanol Vapor-Sensing Behavior of Sol-Gel Electrospun ZnO Nanofibers Using an Indigenous Setup

The calibration is essential for accuracy, repeatability, and continuous trouble-free operation of gas sensors with safety. Most gas sensors are fabricated using metal oxide nanomaterials in different structures such as films, coating, or nanofibers. Therefore, a device in the sensor manufacturing industry is necessary to test, calibrate, and optimize metal oxide structures. In this point of view, a simple device is developed to test and estimate the sensing response, response time, and recovery time of nanostructures. The sol-gel method was used to produce nanofibers through electrospinning. An average fiber diameter of 245 nm was obtained after pyrolysis at 600 °C. The structure and composition of ZnO nanofibers are confirmed by X-ray diffraction, scanning electron microscopy, and Brunauer-Emmett-Teller. The trials were taken using ZnO nanofibers in the presence of acetone and ethanol vapor, and the results were reported. High response (31.74), rapid response (40 s), and recovery (30 s) times have been achieved for ethanol gas to 50 ppm concentration test gas at an optimal temperature of 260 °C. The results obtained from the trials are compared with the literature results, which are in line with the values presented by the various researchers. Due to the low cost, easy maintenance, and accuracy, this device is recommended in metal oxide sensor development industries and laboratories.

Detection and Quantification of Ammonia as the Ammonium Cation in Human Saliva by 1H NMR: A Promising Probe for Health Status Monitoring, with Special Reference to Cancer

Ammonia (NH₃) has been shown to be a key biomarker for a wide variety of diseases, such as hepatic and chronic kidney diseases (CKD), and cancers. It also has relevance to the oral health research area, and, hence, its determination in appropriate biofluids and tissues is of much importance. However, since it contains exchangeable >N-H protons, its analysis via ¹H NMR spectroscopy, which is a widely employed technique in untargeted metabolomic studies, is rendered complicated. In this study, we focused on the ¹H NMR analysis of this biomarker in less invasively collected human saliva samples, and we successfully identified and quantified it as ammonium cation (NH₄⁺) in post-collection acidulated forms of this biofluid using both the standard calibration curve and standard addition method (SAM) approaches. For this purpose, n = 27 whole mouth saliva (WMS) samples were provided by healthy human participants, and all donors were required to follow a fasting/oral environment abstention period of 8 h prior to collection. Following acidification (pH 2.00), diluted WMS supernatant samples treated with 10% (v/v) D₂O underwent ¹H NMR analysis (600 MHz). The acquired results demonstrated that NH₄⁺ can be reliably determined in these supernatants via integration of the central line of its characteristic 1:1:1 intensity triplet resonance (complete spectral range δ = 6.97-7.21 ppm). Experiments performed also demonstrated that any urease-catalysed NH₃ generation occurring post-sampling in WMS samples did not affect the results acquired during the usual timespan of laboratory processing required prior to analysis. Further experiments demonstrated that oral mouth-rinsing episodes conducted prior to sample collection, as reported in previous studies, gave rise to major decreases in salivary NH₄⁺ levels thereafter, which renormalised to only 50-60% of their basal control concentrations at the 180-min post-rinsing time point. Therefore, the WMS sample collection method employed significantly affected the absolute levels of this analyte. The LLOD was 60 μmol/L with 128 scans. The mean ± SD salivary NH₄⁺ concentration of WMS supernatants was 11.4 ± 4.5 mmol/L. The potential extension of these analytical strategies to the screening of other metabolites with exchangeable ¹H nuclei is discussed, as is their relevance to the monitoring of human disorders involving the excessive generation and/or uptake of cellular/tissue material, or altered homeostasis, in NH₃.

Microwave Gas Sensors Based on Electrodeposited Polypyrrole-Nickel Phthalocyanine Hybrid Films

Previous studies have shown that the incorporation of sulfonated metallophthalocyanines into sensitive sensor materials can improve electron transfer and thus species detection. Herein, we propose a simple and easy alternative to the use of generally expensive sulfonated phthalocyanines by electropolymerizing polypyrrole together with nickel phthalocyanine in the presence of an anionic surfactant. The addition of the surfactant not only helps the incorporation of the water-insoluble pigment into the polypyrrole film, but the obtained structure has increased hydrophobicity, which is a key property for developing efficient gas sensors with low sensitivity to water. The obtained results show the effectiveness of the materials tested for the detection of ammonia in the range of 100 to 400 ppm. It is shown by comparing the microwave sensor responses that the film without nickel phthalocyanine (hydrophilic) produces greater variations than the film with nickel phthalocyanine (hydrophobic). These results are consistent with the expected results since the hydrophobic film is not very sensitive to residual ambient water and therefore does not interfere with the microwave response. However, although this excess response is usually a handicap, as it is a source of drift, in these experiments the microwave response shows great stability in both cases.

A nanostructured Al-doped ZnO as an ultra-sensitive room-temperature ammonia gas sensor

Novel chemi-resistive gas sensors with strong detection capabilities operating at room temperature are desirable owing to their extended cycle life, high stability, and low power consumption. The current study focuses on detecting NH3 at room temperature using lower gas concentrations. The co-precipitation technique was employed to produce pure and Al-doped ZnO nanoparticles, which were calcined at 300 °C for three hours. The effect of aluminium (Al) doping on the structural, morphological, optical, and gas-sensing abilities was investigated and reported. The presence of aluminium was confirmed by XRD, EDX, and FTIR spectroscopy. Additionally, to assess the various characteristics of Al-doped ZnO nanoparticles, scanning electron microscopy (SEM), ultraviolet-visible diffuse reflectance spectroscopy (UV-DRS), atomic force microscopy (AFM), and Brunauer-Emmett-Teller (BET) techniques were used. The crystallite size increased from 14.82 to 17.49 nm in the XRD analysis; the SEM pictures showed a flower-like morphology; and the energy gap decreased from 3.240 to 3.210 eV when Al doping was raised from 1 wt% to 4 wt%. AFM studies revealed topographical information with significant roughness in the range of 230-43 nm. BET analysis showed a mesoporous nature with surface areas varying from 25.274 to 14.755 m2/g and pore diameters ranging from 8.34 to 7.00 nm. The sensing capacities of pure and Al-doped ZnO nanoparticles towards methanol (CH3OH), toluene (C7H8), ethanol (C2H5OH), and ammonia (NH3) were investigated at room temperature. The one-wt% Al-doped ZnO sensor demonstrated an ultrafast response and recovery times at one ppm compared to other AZO-based sensors towards NH3.

Breath-by-breath measurement of exhaled ammonia by acetone-modifier positive photoionization ion mobility spectrometry via online dilution and purging sampling

Exhaled ammonia (NH₃) is an essential noninvasive biomarker for disease diagnosis. In this study, an acetone-modifier positive photoionization ion mobility spectrometry (AM-PIMS) method was developed for accurate qualitative and quantitative analysis of exhaled NH₃ with high selectivity and sensitivity. Acetone was introduced into the drift tube along with the drift gas as a modifier, and the characteristic NH₃ product ion peak of (C₃H₆O)₄NH₄⁺ (K₀ = 1.45 cm²/V·s) was obtained through the ion-molecule reaction with acetone reactant ions (C₃H₆O)₂H⁺ (K₀ = 1.87 cm²/V·s), which significantly increased the peak-to-peak resolution and improved the accuracy of exhaled NH₃ qualitative identification. Moreover, the interference of high humidity and the memory effect of NH₃ molecules were significantly reduced via online dilution and purging sampling, thus realizing breath-by-breath measurement. As a result, a wide quantitative range of 5.87-140.92 μmol/L with a response time of 40 ms was achieved, and the exhaled NH₃ profile could be synchronized with the concentration curve of exhaled CO₂. Finally, the analytical capacity of AM-PIMS was demonstrated by measuring the exhaled NH₃ of healthy subjects, demonstrating its great potential for clinical disease diagnosis.

The influence of socioeconomic and environmental determinants on acute myocardial infarction (AMI) mortality from the spatial epidemiological perspective

Plenty of epidemiological approaches have been explored to detect the effects of environmental and socioeconomic factors on acute myocardial infarction (AMI) mortality. Whereas, identifying the influence of potential affecting factors on AMI mortality based on a spatial epidemiological perspective was strongly desired. Moreover, the interaction effects of two potential factors on the diseases were always neglected previously. Here, the Geodetector and geographically & temporally weighted regression model (GTWR) combined with multi-source spatiotemporal datasets were introduced to quantitatively determine the relationship between AMI mortality and potential influencing factors across Xi'an during 2014-2016. Besides, Moran's I was adopted to diagnose the spatial autocorrelation of AMI mortality. Some findings were achieved. The number of AMI mortality cases increased from 5075 in 2014 to 6774 in 2016. Air pollutants, meteorological factors, economic status, and topography factors exhibited a significant effect on AMI mortality. The AMI mortality demonstrated an obvious spatial autocorrelation feature during 2014-2016. POP and PE represented the most obvious impact on AMI mortality, respectively. Moreover, the interaction of any two factors was larger than that of the single factor on AMI mortality, and the factors with the strongest interaction vary according to lag groups and ages. The effects of factors on AMI mortality were POP (- 628.925) > PE (140.102) > RD (79.145) > O₃ (- 58.438) > E_NH₃ (42.370) for male, and POP (- 751.206) > RD (132.935) > E_NH₃ (58.758) > PE (- 45.434) > O₃ (- 21.256) for female, respectively. This work reminds the local government to continuously control air pollution, strengthen urban planning, and improve the health care of the rural areas for alleviating AMI mortality. Meanwhile, the scheme of the current study supplies a scientific reference for examining the effects of potential impact factors on related diseases using the spatial epidemiological perspective.

Photoacoustic detection of ammonia exhaled by individuals with chronic kidney disease

Ammonia (NH₃) has been reported as a breath biomarker for chronic kidney disease (CKD) usually detected at concentrations greater than 0.25 parts per million by volume (ppmV). NH₃ was detected in breath of individuals with CKD through gaseous photoacoustic spectroscopy (PAS). The efficiency of hemodialysis (HD) was demonstrated. Eight volunteers aged between 20 and 60 years and without previous respiratory disease were eligible, among which six were control volunteers (CV) and two volunteers with advanced CKD, named CKDV1 and CKDV2. The presence of CKD was confirmed by the calculation of creatinine clearance (CC) according to the Cockcroft-Gault equation. Before HD, the mean NH₃ concentration exhaled by CKDV1 was 0.9 ± 0.1 ppmV and after HD was 0.20 ± 0.03 ppmV, which demonstrated an efficiency of 76% NH₃ reduction in breath. The CKDV2 exhaled 1.27 ± 0.03 ppmV of NH₃ pre-HD and 0.42 ± 0.08 ppmV post-HD, which resulted in efficiency of about 67%. It was not possible to quantify NH₃ from CV, what led us to infer that all of them exhaled amounts below the detection limit, i.e., 0.20 ppmV. This assumption is underpinned by CC, whose values hovered at 90 ≤ CC ≤ 120 mL/ min, confirming normal renal function.

Sensors for the detection of ammonia as a potential biomarker for health screening

The presence of ammonia within the body has long been linked to complications stemming from the liver, kidneys, and stomach. These complications can be the result of serious conditions such as chronic kidney disease (CKD), peptic ulcers, and recently COVID-19. Limited liver and kidney function leads to increased blood urea nitrogen (BUN) within the body resulting in elevated levels of ammonia in the mouth, nose, and skin. Similarly, peptic ulcers, commonly from H. pylori, result in ammonia production from urea within the stomach. The presence of these biomarkers enables a potential screening protocol to be considered for frequent, non-invasive monitoring of these conditions. Unfortunately, detection of ammonia in these mediums is rather challenging due to relatively small concentrations and an abundance of interferents. Currently, there are no options available for non-invasive screening of these conditions continuously and in real-time. Here we demonstrate the selective detection of ammonia using a vapor phase thermodynamic sensing platform capable of being employed as part of a health screening protocol. The results show that our detection system has the remarkable ability to selectively detect trace levels of ammonia in the vapor phase using a single catalyst. Additionally, detection was demonstrated in the presence of interferents such as carbon dioxide (CO₂) and acetone common in human breath. These results show that our thermodynamic sensors are well suited to selectively detect ammonia at levels that could potentially be useful for health screening applications.